An Improved DTW Method for Human Behavior Recognition

摘要：

　　Human behavior recognition has been widely used in computer vision.However,the accuracy and stability of the recognition algorithm will be affected by the different data acquisition objects and object behavior.To solve this problem,an improved human behavior similarity measure method based on improved dynamic time warping(DTW)is proposed.First,the data of human joints is acquired by Kinect.Then,the path is corrected with DTW algorithm according to the motion distance between the motion to be tested and template.Next,the corrected path is further adjusted via curve fitting.Finally,the behavior similarity between them is obtained by the adjusted path.The experimental results show that the performance of the proposed method is more stable and accurate.

关键词： Human Behavior Recognition Kinect DTW Curve Fitting Behavior Similarity

作者: Shengnan Li Yan Mab Hui Huang Shunbao Li

作者单位: Collage of Information,Mechanical and Electrical Engineering,Shanghai Normal University,Shanghai,China

会议类型: 国际会议

会议名称: 2019年第二届智能系统研究与机电工程国际会议(ISRME 2019) 2019 2nd International Conference on Intelligent Systems Research and Mechatronics Engineering

会议地点: 太原

会议语种:英文

页码: 187-192

在线出版日期: 2019-06-29（万方平台首次上网日期，不代表论文的发表时间）